---
title: "Fatness Over 9000"
author: "Bryan Jenks"
date: "7/30/2020"
output: 
  flexdashboard::flex_dashboard:
    vertical_layout: scroll
    theme: bootstrap
    orientation: rows
    source_code: embed
    social: [ "twitter", "facebook", "menu" ]
    navbar:
      - { title: "About", href: "https://www.bryanjenks.xyz",   align: left }
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r load_libs, echo=F}
library(magrittr)
# Package names
packages <- c("here", "DT", "kableExtra", "tidylog", "esquisse", "flexdashboard", "readr", "ggplot2")

# Install packages not yet installed
installed_packages <- packages %in% rownames(installed.packages())
if (any(installed_packages == FALSE)) {
  install.packages(packages[!installed_packages])
}

# Packages loading
lapply(packages, library, character.only = TRUE) %>%
  invisible()
```

```{r load_data, echo=F}
source(here::here("R","get_data.R")) 
```

# Charts

YEET 

Page 1 {data-navmenu="Menu A" .hidden}
=====================================


Page 2 {data-navmenu="Menu A" data-icon="fa-list"}
=====================================  

Sidebar {.sidebar}
=====================================



Link to [Page 3](#page-3)

Page 3 {data-navmenu="Menu B" data-icon="fa-hashtag"}
=====================================

You can link to a dashboard page with either of the following syntaxes:

[Page 2]

[Page Two](#page-2)

The second syntax is used when you want a custom name for the link 
(rather than just using the page title).

Page 4 {data-navmenu="Menu B" data-icon="fa-list"}
=====================================  

Row {.tabset .tabset-fade data-height=650}
-------------------------------------
    
### Chart 1
    
```{r echo=F}
exercises <- c("calf raise","calf raise (Red)","calf raise (Black)")
data %>%
 filter(!(exercise %in% c("pushup", "bridge", "wall squat", "Superman Hold", 
"Superman", "Superman (Flutter Kicks)"))) %>%
  filter(exercise %in% exercises) %>% 
  # filter(set_number == 1) %>% 
 ggplot() +
 aes(x = date, y = reps_numerator, fill = set_number) +
 geom_line(size = 1L, colour = "#2171b5") +
 scale_fill_gradient() +
 theme_minimal() +
 theme(legend.position = "top") +
 facet_wrap(vars(exercise)) 
```

### Chart 1b

```{r}

  ggplot2::diamonds %>%
  dplyr::filter(cut == "Ideal",
                price > 10000L) %>% 
  DT::datatable()

```

### Chart 1c

```{r echo=F}
flexdashboard::valueBox(max(mtcars$mpg), icon = "fa-pencil") 
```


Row 
-------------------------------------
    
### Chart 2
    
```{r echo=F}

data %>%
 filter(exercise %in% c("pushup", "pistol squat", "pistol squat (lvl 2)")) %>%
 
    filter(reps_numerator >= 1L & reps_numerator <= 56L) %>%
 filter(reps_denominator >= 
    1L & reps_denominator <= 58L) %>%
 ggplot() +
 aes(x = date, y = reps_numerator, colour = reps_numerator) +
 geom_line(size = 1L) +
 scale_color_gradient() +
 labs(x = "Time", y = "Rep Count", title = "Facet Pistol SQ and Pushups", subtitle = "Pushups sans 100 rep aggregated set due to scale skew", caption = "One Month of Training Data", color = "Reps") +
 theme_minimal() +
 facet_wrap(vars(exercise))

```
    
### Chart 3

```{r echo=F}
data %>%
 filter(exercise %in% c("pistol squat (lvl 2)", "pistol squat")) %>%
 filter(reps_numerator >= 
    1L & reps_numerator <= 56L) %>%
 filter(reps_denominator >= 1L & reps_denominator <= 
    58L) %>%
 ggplot() +
 aes(x = reps_numerator, y = reps_denominator, fill = reps_numerator) +
 geom_tile(size = 1L) +
 scale_fill_gradient() +
 labs(x = "Time", y = "Rep Count", title = "Facet Pistol SQ and Pushups", subtitle = "Pushups sans 100 rep aggregated set due to scale skew", caption = "One Month of Training Data") +
 theme_minimal() +
 facet_wrap(vars(exercise))
```

Row 
-------------------------------------

### MUH DATA

```{r}

  ggplot2::diamonds %>%
  dplyr::filter(cut == "Ideal",
                price > 10000L) %>% 
  DT::datatable()

```

# Gauges

Row 
-------------------------------------
    
### Contact Rate

```{r echo=F}
rate <- 91L
gauge(rate, min = 0, max = 100, symbol = '%', gaugeSectors(
  success = c(80, 100), warning = c(40, 79), danger = c(0, 39)
), href="#Page 2")
```

### Average Rating 

```{r echo=F}
rating <- 37.4
gauge(rating, min = 0, max = 50, gaugeSectors(
  success = c(41, 50), warning = c(21, 40), danger = c(0, 20)
))
```

### Cancellations

```{r echo=F}
cancellations <- 7
gauge(cancellations, min = 0, max = 10, gaugeSectors(
  success = c(0, 2), warning = c(3, 6), danger = c(7, 10)
))
```

Row
-------------------------------------

### About dygraphs

This example makes use of the dygraphs R package. The dygraphs
package provides rich facilities for charting time-series data 
in R. You can use dygraphs at the R console, within R Markdown
documents, and within Shiny applications.

### About Me

This example makes use of the dygraphs R package. The dygraphs
package provides rich facilities for charting time-series data 
in R. You can use dygraphs at the R console, within R Markdown
documents, and within Shiny applications.

### About Lorum Ipsum

This example makes use of the dygraphs R package. The dygraphs
package provides rich facilities for charting time-series data 
in R. You can use dygraphs at the R console, within R Markdown
documents, and within Shiny applications.